Characterization of the shape of aggregates using image analysis and machine learning classification tools

Respiratory tract deposition of inhaled 67Ga2O3 particles, both aggregate and near spherical, was studied in one group of 10 Beagle dogs using nose-only exposures to both aerosols. Aggregate particles were produced by vaporization of 67Ga tetramethylheptanedione followed by heat treatment at 1100°C. Near spherical particles were produced by introducing steam at an intermediate temperature (500°C) to allow solubilization of the particles in a droplet before complete oxidation and drying at 1100°C. Particle sizes were 0.10 ± 0.02 μm (σg = 1.6) and 0.11 ± 0.02 μm (σg = 1.8) activity median diffusion diameter for the aggregate and near-spherical particles, respectively. The shape factors were 1.76 and 1.01 for aggregate and near-spherical particles, respectively. Whole body counting and gamma camera imaging techniques were used to determine deposition as a percentage of the inhaled particles. Percentage deposition values for the aggregate and near-spherical particles were, respectively: total respiratory tract, 39 ± 19% and 42 ± 16%; pulmonary, 25 ± 12% and 30 ± 10%. This similarity in deposition patterns shows that deposition data from aggregate particles can be generalized to other ultrafine particles when diffusion diameter is used to characterize particle size.

Rotation-mediated histogenetic aggregation of dissociated cells: A quantifiable approach to cell interactions in vitro

A shape factor to assess the shape of particles using image analysis

Activation and inhibition of mast cells degranulation affect their morphometric parameters

Registration is an essential tool in image analysis. Deep learning based alternatives have recently become popular, achieving competitive performance at a faster speed. However, many contemporary techniques are limited to volumetric representations, despite increased popularity of 3D surface and shape data in medical image analysis. We propose a one-step registration model for 3D surfaces that internalises a lower dimensional probabilistic deformation model (PDM) using conditional variational autoencoders (CVAE). The deformations are constrained to be diffeomorphic using an exponentiation layer. The one-step registration model is benchmarked against iterative techniques, trading in a slightly lower performance in terms of shape fit for a higher compactness. We experiment with two distance metrics, Chamfer distance (CD) and Sinkhorn divergence (SD), as specific distance functions for surface data in real-world registration scenarios. The internalised deformation model is benchmarked against linear principal component analysis (PCA) achieving competitive results and improved generalisability from lower dimensions.

Introduction While IVD strain can be measured, the stress distribution within the disk is dependent on the IVD's material properties and its geometry and must be calculated. The IVD geometry remains incompletely characterized. Prior whole-disk models have been constructed from single IVDs. While this approach ensures that the geometry has a physiological basis, the degree to which results from a single IVD shape can be generalized to the entire population is uncertain. The primary objective of this study, therefore, was to develop a quantitative representation of IVD shape for the population. The approach incorporates a representative average IVD shape from multiple individuals and uses principal components analysis (PCA) to partition the variability of IVD shape into a small number of orthogonal modes of variation. These modes of variation can be adjusted parametrically. Since IVD shape is expected to change with degeneration, each mode of variation was correlated with degeneration grade to isolate degeneration-related shape variability from normal variability between individuals. Materials and Methods Magnetic Resonance Imaging Total 14 postmortem, agarose embedded L3-L4 motion segments (13 M, 1 F - age 69 ± 12 years - Pfirrmann grade 3.3 ± 0.8) underwent MRI (7T Siemens scanner - custom RF coil) using a 3D FLASH sequence (TE/TR = 3.7/9 ms) with ∼200 mm isotropic resolution.1 Image SegmentationBefore segmentation, the MRI images underwent intensity inhomogeneity correction, 50% downsampling, and Gaussian smoothing. Segmentation of the intervertebral disk was done in SNAP.2 The intensity-based region competition active contour tool was used to provide an initial segmentation. Errors in the automatic result were corrected by manual slice-by-slice segmentation. Shape Quantification The shape model was created by PCA of the disk segmentations.3 To make the images amenable to PCA, they were embedded as signed distance functions.3 The mean of the signed distance functions represents the average disk shape, with the residual shape variability captured as offsets from the mean signed distance function. These residuals were analyzed by PCA to produce a new 13-dimensional orthonormal basis for IVD shape. Each basis vector represents a different mode of shape variation. The basis vectors were ordered by the amount of variability that they capture from the original dataset. Following PCA, each disk in the dataset was projected into the new basis as a linear combination of the mean shape and the shape variation basis vectors. To determine which basis vectors represented degeneration-related shape variation, the projection coefficients were then correlated to Pfirrmann grade. Finally, to supplement the PCA-derived representation, the disk shapes were summarized by geometric measures: width, (left to right), depth (anterior-posterior distance at the mid-sagittal plane), height (averaged over the entire IVD), and axial-plane area. Results The first basis vector M1 represented an order of magnitude more variance than any other basis vector. Relative to M1, the second basis vector M2 captured 11% as much variance; M3, 9%; M4, 7%; M5, 5%; M6, 3%. Basis vectors 7 to 13 captured less than 2% as much variance as basis vector M1. Given the low variances associated with basis vectors M2 to M13 relative to basis vector M1, it is possible to represent IVD shape by the basis vector M1 coefficient w1 alone and still capture the majority of the population's IVD shape variation. Examination of the shapes produced by adding and subtracting one standard deviation of basis vector M1 from the mean shape reveals that basis vector M1 primarily controls lateral disk bulging, with little change in disk height. The basis vector M1 was also the only basis vector to show a significant correlation to degeneration as measured by Pfirrmann grade. None of the basis vectors were significantly correlated with age. Conclusion The objective of obtaining a low-dimensional representation of IVD shape was met. IVD shape variation was dominated by a single lateral bulging-related component, which was also correlated to degeneration grade. The low dimensionality of the shape representation makes it amenable to human manipulation, permitting straightforward modeling of a representative sampling of IVD shapes for example, for finite element analysis. The shape representation can also be used directly as a shape before Bayesian image segmentation of low-detail IVD images, for example, in vivo MRI. Further work is required to establish causation between degeneration and shape changes. Acknowledgment NIH grant R01 AR05005. I confirm having declared any potential conflict of interest for all authors listed on this abstract Yes Disclosure of Interest None declared Pfirrmann CW, et al. Spine 2001;26:1873 Yushkevich PA, et al. NeuroImage 2006;31:1116 Tsai A, et al. IEEE Transaction Medical Imaging 2003;22:137

Automated determination of poplar chip size distribution based on combined image and multivariate analyses

The advancement of high-content optical microscopy has enabled the acquisition of very large three-dimensional (3D) image datasets. The analysis of these image volumes requires more computational resources than a biologist may have access to in typical desktop or laptop computers. This is especially true if machine learning tools are being used for image analysis. With the increased amount of data analysis and computational complexity, there is a need for a more accessible, easy-to-use, and efficient network-based 3D image processing system. The distributed and networked analysis of volumetric image data (DINAVID) system was developed to enable remote analysis of 3D microscopy images for biologists. We present an overview of the DINAVID system and compare it to other tools currently available for microscopy image analysis. DINAVID is designed using open-source tools and has two main sub-systems, a computational system for 3D microscopy image processing and analysis and a 3D visualization system. DINAVID is a network-based system with a simple web interface that allows biologists to upload 3D volumes for analysis and visualization. DINAVID enables the image access model of a center hosting image volumes and remote users analyzing those volumes, without the need for remote users to manage any computational resources. The DINAVID system, designed and developed using open-source tools, enables biologists to analyze and visualize 3D microscopy volumes remotely without the need to manage computational resources. DINAVID also provides several image analysis tools, including pre-processing and several segmentation models.

Aggregate shape properties can greatly influence the overall performance of asphalt mixtures. In this study, shape-controlled aggregates were fabricated and used in porous asphalt mixture (PAM) to assess the effect of aggregate shape properties on the performance of PAM. Three shapes of the aggregates were fabricated, namely cube, cylinder, and sphere. Two parameters, shape factor and sphericity index, were used to define the aggregate shape properties. Results of discrete-element method (DEM) simulation and laboratory measurements were compared to obtain a better understanding on the effect of aggregate shape on the performance of PAM. The results indicated that aggregate shape properties have notable effect on the overall performance of PAM. Spherical aggregates need only a low compaction effort to achieve the design voids-in-total-mix (VTM). For aggregates with the same shape factor, the overall mechanistic properties of PAM generally decrease with increasing sphericity of the aggregates.

Image analysis tools are currently in use for a variety of applications in the fields of forensics and security printing. Objective, quantitative data allow for characterization and comparison of a variety of image attributes.In forensics, document examiners can use quantitative image analysis systems in authentication, detection and analysis of forgeries, counterfeits and altered documents. Statistical analysis enables population characterization that can help in forgery detection and supports the potential for source identification. In security printing, image analysis tools can be applied to measure the quality of printed output and assess wear for bank notes.Flexible hardware options allow for a broad application of image quality measurements in a variety of image analysis situations. Camera and scanner-based image quality systems can be used for quantitative analysis of image content. A laser-based system can be used for height and depth profiling. Oblique angle illumination and scanning can be used for impression detection. A flatbed scanner can be used in transmission mode for the evaluation of bank note wear and for watermark analysis.In this paper, we will be discussing the use of a variety of hardware configurations for image analysis in forensics and security printing.

Received: 2018-06-07 | Accepted: 2018-06-19 | Available online: 2018-06-30 https://doi.org/10.15414/afz.2018.21.02.77-83 The aim of this study was to distinguishing between kernels of maize hybrids by the use of image analysis tools. We analyzed 10 registered Zea mays L. hybrids (5 – dent, 2 – semi-flint to flint, and 3 – semi-flint to dent type). Different parameters on ventral, dorsal, corolla side, and lateral side cross section of kernel were measured. Sample per each hybrid comprised 50 maize kernels. Acquired bio-images were processed by software Zeiss AxioVision Rel. 4.8. We analyzed the segmented regions of interest on the kernels. The data for area (mm 2 ), height and width (mm) were gathered from these regions. The hybrid ZE EDOX significantly differed (p < 0.05) from all other hybrids almost in all traits. It is the hybrid with the smallest area of the whole kernel, floury endosperm proportion, and depressed part on corolla. The new trait the area of the depressed part on the kernel corolla was measured. The hybrids with smaller proportion of floury endosperm had smaller area of depressed part, and vice versa. The image analysis methods can usefully contribute to selection of proper hybrids for different types of use. Keywords: maize, Zea mays L., kernel, image analysis References BLASCHKE, T. et al. (2014) Geographic Object-Based Image Analysis – Towards a new paradigm. In ISPRS Journal of Photogrammetry and Remote Sensing, vol. 87, pp. 180–191. https://doi.org/10.1016/j.isprsjprs.2013.09.014 DE CARVALHO, M. L. M., VAN AELST, A. C., VAN ECK, J. W., HOEKSTRA, F. A. (1999) Pre-harvest stress cracks in maize (Zea mays L.) kernels as characterized by visual, X-ray and low temperature scanning electron microscopical analysis: effect on kernel quality. In Seed Science Research, vol. 9, pp. 227–236. DELL´AQUILA, A. (2006) Computerised seed imaging: a new tool to evaluate germination quality. In Communications in Biometry and Crop Science, vol. 1, no. 1, pp. 20–31. ERASMUS, C. (2003) Maize kernel translucency measurement by Image Analysis and its relationship to vitreousness and dry milling performance. PhD thesis. Pretoria: University of Pretoria. FOX, G. and MANLEY, M. (2009) Hardness methods for testing maize kernels. In Journal of Agricultural and Food Chemistry, vol. 57, no. 13, pp. 5647–5657. doi: https://doi.org/10.1021/jf900623w GLASBEY, C. A. and HORGAN, G. W. (2001) Image analysis in agriculture research. In Quantitative Approaches in System Analysis, special issue, vol. 23, pp. 43–54. GUELPA, A., DU PLESIS, A., KIDD, M., MANLEY, M. (2015) Nondestructive estimation of maize (Zea mays L.) kernel hardness by means of an X-ray micro-computed tomography (μCT) density calibration. In Food and Bioprocess Technology, vol. 8, no. 6, pp. 1419–1429. JANDA, J. and MICHALEC, V. (1982) Mayze. Bratislava: Priroda. 408 p. MUTTERER, J. and ZINCK, E. (2013) Quick‐and‐clean article figures with FigureJ. In Journal of Microscopy, vol. 252, pp. 89– 91. doi: https://doi.org/10.1111/jmi.12069 ROBUTTI, J. L., HOSENEY, R. C. and WASSOM, C. E. (1974). Modified opaque-2 corn endosperms. ll. Structure viewed with a scanning electron microscope. In American Association of Cereal Chemists, vol. 51, pp. 173–180. RODRIGUEZ-PULIDO, F. J. et al. (2012) Ripeness estimation of grape berries and seeds by image analysis. In Computers and Electronics in Agriculture, vol. 82, pp. 128–133. SCHINDELIN, J., RUEDEN, C. T., HINER, M. C., ELICEIRI, K. W. (2015) The ImageJ ecosystem: An open platform for biomedical image analysis. In Mol. Reprod. Dev., vol. 82, pp. 518–529. doi: https://doi.org/10.1002/mrd.22489 UCHIDA, S. (2013) Image processing and recognition for biological images. In Development, growth and differentiation, vol. 55, pp. 523–549. doi: https://doi.org/10.1111/dgd.12054 WATSON, S. A. (1987) Structure and composition. In WATSON, S. A. and RAMSTAD, P. E. (Eds.). Corn chemistry and technology. St. Paul: American Association of Cereal Chemists. WIWART M. et al. (2012) Identification of hybrids of spelt and wheat and their parental forms using shape and color descriptors. In Computers and Electronics in Agriculture, vol. 83, pp. 68–76. https://doi.org/10.1016/j.compag.2012.01.015

Meso-scale modelling of static and dynamic tensile fracture of concrete accounting for real-shape aggregates

Morphological properties of mineral aggregates are known to affect pavement and railroad track mechanistic behavior and performance significantly in relation to strength, modulus, and permanent deformation. With imaging technology, an objective and accurate measurement of aggregate particle size and shape properties can be obtained in a rapid, reliable, and automated fashion. But these advances in aggregate imaging must be brought to project sites and quarries in the field. This paper introduces field image-acquisition and image-processing techniques for extraction and analyses of size and shape properties of individual aggregate particles. Referred to as segmentation techniques, image-processing methods developed in this study analyzed two-dimensional field images of aggregates captured by a digital single-lens reflex camera. The segmented aggregate images were fed into the validated University of Illinois aggregate image analyzer to quantify particle size and shape properties by means of its image-processing algorithms for flat-and-elongated ratio, angularity index, and surface texture index. The developed method successfully determined the properties of coarse-aggregate samples collected from various depths in a layer of railroad track ballast. The promising preliminary results indicate that these segmentation techniques could be considered in the field for capturing several aggregate particles rapidly and reliably in a single image so that (a) size and shape properties of individual particles could be analyzed and (b) both spatial property variability and property changes with layer depth and usage (i.e., property degradation in time) could be evaluated under service loading.

P-glycoprotein is implicated in clinical drug resistance; thus, rapid quantitative analysis of its expression and activity is of paramout importance to the design and success of novel therapeutics. The scope for the application of quantitative imaging and image analysis tools in this field is reported here at "proof of concept" level. P-glycoprotein expression was utilized as a model for quantitative immunofluorescence and subsequent spatial intensity distribution analysis (SpIDA). Following expression studies, p-glycoprotein inhibition as a function of verapamil concentration was assessed in two cell lines using live cell imaging of intracellular Calcein retention and a routine monolayer fluorescence assay. Intercellular and sub-cellular distributions in the expression of the p-glycoprotein transporter between parent and MDR1-transfected Madin-Derby Canine Kidney cell lines were examined. We have demonstrated that quantitative imaging can provide dose-response parameters while permitting direct microscopic analysis of intracellular fluorophore distributions in live and fixed samples. Analysis with SpIDA offers the ability to detect heterogeniety in the distribution of labeled species, and in conjunction with live cell imaging and immunofluorescence staining may be applied to the determination of pharmacological parameters or analysis of biopsies providing a rapid prognostic tool.

We report here the identification of a previously unknown transcription regulatory element for heat shock (HS) genes in Caenorhabditis elegans. We monitored the expression pattern of 11,917 genes from C. elegans to determine the genes that were up-regulated on HS. Twenty eight genes were observed to be consistently up-regulated in several different repetitions of the experiments. We analyzed the upstream regions of these genes using computational DNA pattern recognition methods. Two potential cis-regulatory motifs were identified in this way. One of these motifs (TTCTAGAA) was the DNA binding motif for the heat shock factor (HSF), whereas the other (GGGTGTC) was previously unreported in the literature. We determined the significance of these motifs for the HS genes using different statistical tests and parameters. Comparative sequence analysis of orthologous HS genes from C. elegans and Caenorhabditis briggsae indicated that the identified DNA regulatory motifs are conserved across related species. The role of the identified DNA sites in regulation of HS genes was tested by in vitro mutagenesis of a green fluorescent protein (GFP) reporter transgene driven by the C. elegans hsp-16-2 promoter. DNA sites corresponding to both motifs are shown to play a significant role in up-regulation of the hsp-16-2 gene on HS. This is one of the rare instances in which a novel regulatory element, identified using computational methods, is shown to be biologically active. The contributions of individual sites toward induction of transcription on HS are nonadditive, which indicates interaction and cross-talk between the sites, possibly through the transcription factors (TFs) binding to these sites.